Movements of individuals within and among populations help to maintain genetic variability and population viability. Therefore, understanding landscape connectivity is vital for effective species conservation. The snow leopard is endemic to mountainous areas of Central Asia and occurs within 12 countries. We assess potential connectivity across the species’ range to highlight corridors for dispersal and genetic flow between populations, prioritizing research and conservation action for this wide-ranging, endangered top-predator. We used resistant kernel modeling to assess snow leopard population connectivity across its global range. We developed an expert-based resistance surface that predicted cost of movement as functions of topographical complexity and land cover. The distribution of individuals was simulated as a uniform density of points throughout the currently accepted global range. We modeled population connectivity from these source points across the resistance surface using three different dispersal scenarios that likely bracket the lifetime movements of individual snow leopard: 100km, 500km and 1000km. The resistant kernel models produced predictive surfaces of dispersal frequency across the snow leopard range for each distance scenario. We evaluated the pattern of connectivity in each of these scenarios and identified potentially important movement corridors and areas where connectivity might be impeded. The models predicted two regional populations, in the north and south of the species range respectively, and revealed a number of potentially important connecting areas. Discrepancies between model outputs and observations highlight unsurveyed areas of connected habitat that urgently require surveying to improve understanding of the global distribution and ecology of snow leopard, and target land management actions to prevent population isolation. The connectivity maps provide a strong basis for directed research and conservation action, and usefully direct the attention of policy makers.